A Transnational Analysis of Elderly European Wealth Distributions: Developing and Testing New Methodologies within the new Household Financial and Consumption Survey

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Citation

Gaylard, D. M. (2017). A Transnational Analysis of Elderly European Wealth Distributions: Developing and Testing New Methodologies within the new Household Financial and Consumption Survey (Thesis, Master of Social Sciences (MSocSc)). University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/11775

Abstract

Transnational wealth inequality is an expanding field of study. However, the field has many limitations especially relating to problems of data availability, methodologies used, and the very limited pool of existing transnational literature. Alongside these basic limitations is a predominating focus on populations as a whole that correspond with a dearth of studies concerned specifically with elderly wealth distributions.

This thesis’ objective is to tackle these three problematic areas in the field, but with a specific focus on the elderly. In particular, new methodologies for analysing transnational distributions of wealth are explored and developed. These new methodologies are then tested within the Household Financial and Consumption Survey environment specifically focusing on the elderly population. This new survey provides an extensive high quality database on household financial characteristics that are pivotal to transnational and sub-cohort focused analysis.

The analysis generates several results. The first is a tested framework of a multifaceted approach for describing wealth distributions. This approach counters the widespread habit of using summary statistics which do not fully describe distributions. The results also provide evidence for two distinct macro distributions of wealth within the countries observed. These distributions represent two ends on a spectrum which contains all the possible wealth distribution shapes.

The combination of developing new methodological tools of analysis and testing them within a new data environment contribute significantly to the field. These new tools will allow for a standardised view providing deep level analysis which is still applicable to a large dataset.